Udemy - Machine Learning Models With Fastapi, Streamlit And Docker

seeders: 6
leechers: 7
updated:

Download Fast Safe Anonymous
movies, software, shows...

Files

[ DevCourseWeb.com ] Udemy - Machine Learning Models With Fastapi, Streamlit And Docker
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 1 - Introduction
    • 1 - Introduction and App Overview.mp4 (21.7 MB)
    • 2 - FastAPI and Streamlit for Machine Learning Overview.mp4 (13.5 MB)
    • 3 - Docker Installation Guide.mp4 (25.4 MB)
    • 4 - Final Code.html (0.4 KB)
    • src_code free_images
      • gabriel-ramos.jpg (2.3 MB)
      • man_jumping.jpg (1.5 MB)
      style-transfer backend
      • Dockerfile (0.3 KB)
      • config.py (0.3 KB)
      • inference.py (1.1 KB)
      • main.py (1.5 KB)
      • models
        • candy.t7 (14.8 MB)
        • composition_vii.t7 (27.1 MB)
        • feathers.t7 (17.6 MB)
        • la_muse.t7 (24.3 MB)
        • mosaic.t7 (17.6 MB)
        • starry_night.t7 (24.3 MB)
        • the_scream.t7 (17.6 MB)
        • the_wave.t7 (24.3 MB)
        • udnie.t7 (10.7 MB)
      • requirements.txt (0.1 KB)
        • docker-compose.yml (0.3 KB)
        • download_models.sh (0.5 KB)
        • frontend
          • Dockerfile (0.2 KB)
          • main.py (1.8 KB)
          • requirements.txt (0.0 KB)
          storage
          • 00d3a938-cdc9-4b94-9819-b12bb3505239.jpg (126.4 KB)
          • 5fa5d40f-740b-4e8f-8dfb-c83af106f62c.jpg (169.8 KB)
          • 5fa5d40f-740b-4e8f-8dfb-c83af106f62c_composition_vii.jpg (212.7 KB)
          2 - FastAPI and Docker Backend
          • 5 - Project Setup.mp4 (45.5 MB)
          • 6 - FastAPI Backend and Image Transformation Functionality.mp4 (132.3 MB)
          • 7 - Docker Container Setup.mp4 (23.3 MB)
          3 - Streamlit and Docker Frontend
          • 8 - Developing the Streamlit User Interface.mp4 (54.7 MB)
          • 9 - Docker Compose Setup.mp4 (48.7 MB)
          4 - Asynchronous Model Serving
          • 10 - Asynchronous Model Serving with FastAPI.mp4 (66.9 MB)
          • 11 - Updating the UI to respond to the async server.mp4 (61.7 MB)
          5 - Conclusion
          • 12 - Conclusion and Final Remarks.mp4 (7.7 MB)
          • 13 - Final Code.html (0.4 KB)
          • src_code free_images
            • gabriel-ramos.jpg (2.3 MB)
            • man_jumping.jpg (1.5 MB)
            style-transfer backend
            • Dockerfile (0.3 KB)
            • config.py (0.3 KB)
            • inference.py (1.1 KB)
            • main.py (1.5 KB)
            • models
              • candy.t7 (14.8 MB)
              • composition_vii.t7 (27.1 MB)
              • feathers.t7 (17.6 MB)
              • la_muse.t7 (24.3 MB)
              • mosaic.t7 (17.6 MB)
              • starry_night.t7 (24.3 MB)
              • the_scream.t7 (17.6 MB)
              • the_wave.t7 (24.3 MB)
              • udnie.t7 (10.7 MB)
            • requirements.txt (0.1 KB)
              • docker-compose.yml (0.3 KB)
              • download_models.sh (0.5 KB)
              • frontend
                • Dockerfile (0.2 KB)
                • main.py (1.8 KB)
                • requirements.txt (0.0 KB)
                storage
                • 00d3a938-cdc9-4b94-9819-b12bb3505239.jpg (126.4 KB)
                • 5fa5d40f-740b-4e8f-8dfb-c83af106f62c.jpg (169.8 KB)
                • 5fa5d40f-740b-4e8f-8dfb-c83af106f62c_composition_vii.jpg (212.7 KB)
                • Bonus Resources.txt (0.4 KB)

Description

Machine Learning Models With Fastapi, Streamlit And Docker



https://DevCourseWeb.com

Published 3/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 764.33 MB | Duration: 1h 4m

Learn how to serve a machine learning model with FastAPI, Streamlit and Docker

What you'll learn
Develop an asynchronous API with Python and FastAPI
Serve up a machine learning model with FastAPI
Develop a UI with Streamlit
Containerize FastAPI and Streamlit with Docker
Leverage asyncio to execute code in the background outside the request/response flow

Requirements
Intermediate Python Skills
Intermediate Docker Skills



Download torrent
866.8 MB
seeders:6
leechers:7
Udemy - Machine Learning Models With Fastapi, Streamlit And Docker


Trackers

tracker name
udp://tracker.torrent.eu.org:451/announce
udp://tracker.tiny-vps.com:6969/announce
http://tracker.foreverpirates.co:80/announce
udp://tracker.cyberia.is:6969/announce
udp://exodus.desync.com:6969/announce
udp://explodie.org:6969/announce
udp://tracker.opentrackr.org:1337/announce
udp://9.rarbg.to:2780/announce
udp://tracker.internetwarriors.net:1337/announce
udp://ipv4.tracker.harry.lu:80/announce
udp://open.stealth.si:80/announce
udp://9.rarbg.to:2900/announce
udp://9.rarbg.me:2720/announce
udp://opentor.org:2710/announce
µTorrent compatible trackers list

Download torrent
866.8 MB
seeders:6
leechers:7
Udemy - Machine Learning Models With Fastapi, Streamlit And Docker


Torrent hash: 06AA0951BA7280D967C6AFDB352A4E1EE084AE00